High-speed analog simulation of CMOS vision chips using explicit integration techniques on many-core processors
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Desarrollo de sistemas y circuitos electrónicos y microelectrónicosKnowledge Area
ElectrónicaSponsors
This work has been partially funded by Spanish government through project RTI2018-097088-B-C33 (MINECO/FEDER, UE) and by EPSRC (the UK Engineering and Physical Sciences Research Council) under grant EP/N0317681/1. The research stay at University of Southampton (UK) has been supported by Ministerio de Educación, Cultura y Deporte within the “Programa Estatal de Promoción del Talento y su Empleabilidad en I+D+i, Subprograma Estatal de Movilidad, del Plan Estatal de I+D+I” under grant PRX18/00565.Realizado en/con
University of Southampton (UK)Publication date
2019-09-01Publisher
IEEEBibliographic Citation
G. Domenech-Asensi and T. J. Kazmierski, "High-speed analog simulation of CMOS vision chips using explicit integration techniques on many-core processors," 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), Grenoble, France, 2020, pp. 646-64Peer review
SiKeywords
Simulation accelerationState-space technique
Many-core
GPU
CMOS imager
Abstract
This work describes a high-speed simulation technique of analog circuits which is based on the use of statespace equations and an explicit integration method parallelised on a multiprocessor architecture. The integration step of
such method is smaller than the one required by an implicit simulation technique based on Newton–Raphson iterations.
However, given that explicit methods do not require the computation of time-consuming matrix factorizations, the overall
simulation time is reduced. The technique described in this work has been implemented on a NVIDIA general purpose
GPU and has been tested simulating the Gaussian filtering operation performed by a smart CMOS image sensor. Such
devices are used to perform computation on the edge and include built-in image processing functions. Among those, the
Gaussian filtering is one of the most common functions, since it is a basic task for early vision processing. These smart
sensors are increasingly complex and hence the time required ...
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